As some people age, their bones may become weak, brittle, and break easily. This condition is called osteoporosis. To treat osteoporosis, doctors often prescribe drugs called nitrogen-containing bisphosphonates (NBPs). These drugs destroy cells called osteoclasts, which break down bone. This helps restore bone mass. To kill osteoclasts, the drugs must enter these cells. First, they must pass through an oily protective layer called a membrane. It is not completely clear how NBPs, which prefer to stay in water-like environments, can cross this oily membrane and enter osteoclasts.

Understanding how NBPs cross the membrane is important to ensure the drugs work effectively. If NBPs do not efficiently cross the membrane, they will not work properly and may cause harmful side effects. Many patients who take NBPs suffer from side effects such as abnormal fractures.

Now, Yu et al. show that two proteins help NBPs cross the membrane. In the experiments, proteins were removed from human cancer cells one at a time using a technique called CRISPRi. CRISPRi enabled the researchers to systematically turn off the genes for each protein and track what affect this had on the NBPs’ ability to cross the membrane. When one of the two genes called SLC37A3 and ATRAID was turned off, NBPs could not get into cells. The protein produced by the SLC37A3 gene opens a gate in the cell membrane allowing NBPs to enter osteoclasts. The protein made by the ATRAID gene helps this gate protein, and without it, the SLC37A3 proteins are unstable and NBPs cannot enter.

Some people have variations of the SLC37A3 and ATRAID genes. Testing whether these genetic variations may alter NBPs’ ability to cross the membrane of osteoclasts in mice, might one day help physicians predict which patients with have side effects.

N-BPs are the most commonly prescribed drugs used to treat osteoporosis (Drake et al., 2008). They have two negatively charged phosphonate groups that bind to hydroxyapatite crystals with high affinity and enable efficient accumulation of N-BPs on the bone surface (Drake et al., 2008). Osteoclasts, the major cell type responsible for bone resorption, release N-BPs from the bone matrix by dissolving bone mineral and then take up N-BPs through fluid-phase endocytosis (Drake et al., 2008; Thompson et al., 2006). N-BPs subsequently inhibit farnesyl diphosphate synthase (FDPS) in the mevalonate pathway and reduce protein prenylation, an essential post-translational lipid modification required for the function of numerous proteins such as Ras, Rab and Rho, thereby inducing apoptosis in osteoclasts and diminishing their bone-resorption activities (Drake et al., 2008; Dunford et al., 2001; Fisher et al., 2000; Hughes et al., 1995; Kavanagh et al., 2006; Luckman et al., 1998a; Luckman et al., 1998b; van Beek et al., 1999). However, it is not known how highly charged N-BPs exit the endocytic pathway to target FDPS, which is localized to the cytosol and peroxisomes (Martín et al., 2007). It has been proposed that the acidification of endocytic compartments might neutralize the negative charges on the phosphonate groups and allow N-BPs to diffuse across the vesicle membrane (Thompson et al., 2006), but this model does not address the issue that the amine groups in N-BPs become positively charged in acidic environments. An alternative model is that a transporter exists that facilitates the exit of N-BPs from endocytic vesicles.

To gain further insight into the mechanism of action of N-BPs, including the mechanism by which N-BPs are delivered to their molecular target, we implemented an unbiased genome-wide screening approach based on CRISPR-mediated interference (CRISPRi) (Figure 1A) (Gilbert et al., 2014). We transduced a genome-scale CRISPRi single-guide RNA (sgRNA) library into K562 human myeloid leukemia cells that stably express a dCas9-KRAB fusion protein, which functions as an sgRNA-guided transcription inhibitor. The cells were split into a population treated with alendronate (ALN), a representative N-BP, and an untreated control population. Through deep sequencing, we quantified the enrichment/depletion of each sgRNA in the treated population compared to the control population (Figure 1B, Figure 1—figure supplement 1A), and designated the target genes of those sgRNAs enriched in the treated population as resistance hits and those depleted as sensitizing hits (Figure 1B, Figure 1—figure supplement 1B and Supplementary file 1). Consistent with the current model for the action of N-BPs, enzymes, co-factors, and regulators of the mevalonate pathway are enriched in top hits (Figure 1C–D and Figure 1—figure supplement 1C–D). Particularly, in accordance with the model that N-BPs induce cell death through inhibiting the enzymatic activities of FDPS and GGPPS1 (Drake et al., 2008), silencing of FDPS and GGPPS1 strongly sensitized cells to ALN (Figure 1C–D). However, in contradiction with the current model of N-BP action, we observed that silencing of numerous enzymes in the pathway upstream of FDPS in fact conferred strong resistance to ALN (Figure 1D). A recent genome-wide genetic interaction study may resolve this paradox (Horlbeck et al., unpublished). That work demonstrated that isopentenyl-5-pyrophosphate (IPP), the substrate of FDPS, is a toxic intermediate that interferes with DNA synthesis and causes DNA damage, suggesting that inhibition of enzymes upstream of FDPS protects cells from ALN by preventing ALN-induced accumulation of IPP.

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Amongst the resistance hits not known to be involved in the mevalonate pathway, the gene that conferred the strongest resistance was SLC37A3 (Figure 1C), which is predicted to encode a membrane protein with 12 transmembrane segments (Chou et al., 2013). SLC37A3 also appeared as a top resistance hit in a second CRISPRi screen using zoledronate, another representative N-BP, as the selection agent (Figure 1—figure supplement 1E and Supplementary file 2), further supporting its role in the mechanism of action of N-BPs. SLC37A3 is predicted based on sequence homology to be a glucose-6-phosphate/phosphate antiporter (Chou et al., 2013). However, it has been demonstrated that SLC37A3 in fact lacks this predicted activity (Pan et al., 2011). To the best of our knowledge, the physiological function of SLC37A3 has remained elusive. Intriguingly, a recent human protein interactome study reported an interaction between SLC37A3 and ATRAID (Huttlin et al., 2017), a type I transmembrane protein that was identified as an N-BP target in a previous work (Surface et al., unpublished) and our zoledronate CRISPRi screen (Figure 1—figure supplement 1E), suggesting SLC37A3 and ATRAID might be functionally related.

To investigate the roles of SLC37A3 and ATRAID in the action of N-BPs, we generated SLC37A3-knockout (SLC37A3^KO) and ATRAID-knockout (ATRAID^KO) cells in K562 cells, human embryo kidney (HEK) 293 T cells and murine macrophage-like RAW 264.7 cells (Figure 2—figure supplement 1A–E) (Surface et al., unpublished; Ran et al., 2013), with K562 and HEK 293 T cells serving as human cell models that represent distinct lineages, and RAW 264.7 macrophages as a mouse cell model that can be differentiated into mature osteoclasts (Collin-Osdoby and Osdoby, 2012). Consistent with the CRISPRi screen and our previous results, knockout of SLC37A3 and ATRAID in all cell types conferred resistance to ALN (Figure 2A–C) (Surface et al., unpublished). Similarly, mature osteoclasts differentiated from knockout RAW cells are more resistant to ALN compared to those differentiated from wild-type cells (Figure 2D and Figure 2—figure supplement 2A) (Surface et al., unpublished). We also measured the reduction in protein prenylation as a readout of N-BP toxicity and verified that ALN treatment had significantly less of an effect on protein prenylation in SLC37A3^KO and ATRAID^KO cells compared to wild-type cells (Figure 2E). Complementation with epitope-tagged SLC37A3 or either isoform of ATRAID (a short isoform, UniProt Q6UW56-1, and a long isoform, UniProt Q6UW56-3) in SLC37A3^KO or ATRAID^KO HEK 293 T cells, respectively, restored sensitivity to ALN (Figure 2—figure supplement 2B–D), confirming that the resistance to ALN observed in the knockout cells is indeed caused by the lack of SLC37A3 or ATRAID expression, and that the epitope-tagged versions of the two proteins are functional.

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The knockout cells are also resistant to N-BPs other than ALN (Figure 2—figure supplement 2E) but not to non-nitrogen-containing bisphosphonates (non-N-BPs), which do not target FDPS (Figure 2—figure supplement 2F) (Drake et al., 2008). Interestingly, knockout of SLC37A3 and ATRAID did not protect cells from lovastatin (LOV), a statin drug that also targets the mevalonate pathway (Figure 2—figure supplement 2G–I) (Tiwari and Khokhar, 2014). The distinctive responses of SLC37A3^KO and ATRAID^KO cells to N-BPs, non-N-BPs, and LOV indicate that the roles of SLC37A3 and ATRAID in the mechanism of action of N-BPs are not related to the mevalonate pathway but are instead specific to N-BPs. As knockout of SLC37A3 and ATRAID in different cell types conferred similar responses, we focused on HEK 293 T cells for further studies as they host various tools for molecular biology.

To probe the epistatic relationship between the two genes, we generated double knockout (ATRAID^KO; SLC37A3^KO, abbreviated as KO²) cells (Figure 2—figure supplement 1F). We observed that SLC37A3^KO cells are more resistant to ALN compared to ATRAID^KO cells, and the knockout of ATRAID in addition to SLC37A3 did not further protect cells from the drug (Figure 2F and Figure 2—figure supplement 2J), indicating that ATRAID and SLC37A3 are indeed functionally related and that SLC37A3 is epistatic to ATRAID.

Next, we investigated the mechanism underlying the observed functional relationship between ATRAID and SLC37A3. As protein localization can often provide clues to protein function and functionally linked proteins frequently share subcellular distribution patterns, we expressed functional, epitope-tagged SLC37A3 and ATRAID (Figure 2—figure supplement 2B–C) and characterized their localization with immunofluorescence (IF). We confirmed that epitope-tagged SLC37A3 and ATRAID are not over-expressed (Figure 3—figure supplement 1A). We observed that SLC37A3 co-localizes with LAMP2, a lysosomal marker, but not with Na⁺/K⁺-ATPase or EEA1, which mark the plasma membrane and early endosomes, respectively (Figure 3A,B and Figure 3—figure supplement 1C). Consistent with a previous report (Ding et al., 2015), both isoforms of ATRAID also predominantly localize to lysosomes but not to the plasma membrane or early endosomes (Figure 3C–D and Figure 3—figure supplement 1D,F–H). When we co-expressed functional and epitope-tagged SLC37A3 and ATRAID (Figure 3—figure supplement 1A–B), we observed that both isoforms of ATRAID predominantly co-localize with SLC37A3 (Figure 3E and Figure 3—figure supplement 1E). To investigate whether the observed co-localization between SLC37A3 and ATRAID represents a physical interaction, we performed reciprocal co-immunoprecipitation (co-IP) experiments in HEK 293 T cells over-expressing the two proteins. We detected an interaction between SLC37A3 and ATRAID in both pull-down directions (Figure 3F), confirming that SLC37A3 and ATRAID physically interact, likely forming a lysosomal complex.

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As it has been reported that the expression levels of certain solute carriers depend on the presence of accessory proteins (Makrides et al., 2014), we investigated the possibility that the functional relationship between ATRAID and SLC37A3 is due to the impaired expression of SLC37A3 in the absence of ATRAID. Indeed, when we expressed SLC37A3 in the KO² cells, we observed a substantial decrease in the protein level of SLC37A3 compared to that when expressed in the SLC37A3^KO background (Figure 3G and Figure 3—figure supplement 2A), even though the mRNA levels of SLC37A3 in both backgrounds are similar (Figure 3—figure supplement 1A). The protein level of SLC37A3 was restored by complementation with either isoform of ATRAID (Figure 3G). (Note that the reduction in SLC37A3 expression in the absence of ATRAID is not clearly observed in Figure 3F due to the over-expression of SLC37A3. Indeed, in samples analyzed in Figure 3F, SLC37A3 exists predominantly in an un-glycosylated form, suggesting saturation of machineries required for the post-translational processing of SLC37A3 (compare Figure 3F and G, also see discussion below).) In reciprocity, we also observed reduced protein levels of both isoforms of ATRAID in the KO² background that cannot be explained by changes in transcript levels (Figure 3H, Figure 3—figure supplement 2B–C and Figure 3—figure supplement 1A). As the translation efficiency of SLC37A3 transcripts is not significantly altered in the absence of ATRAID (Figure 3—figure supplement 2D–E), the decreased SLC37A3 protein level in the KO² background is likely caused by shortened protein half-life, suggesting that ATRAID and SLC37A3 are mutually dependent for their stability. Intriguingly, the deletion of ATRAID also altered the glycosylation pattern of SLC37A3. In the absence of ATRAID, the mature, glycosylated population of SLC37A3 (around 50kD) became undetectable, whereas a population of un-glycosylated SLC37A3 (around 40kD) emerged (Figure 3G and Figure 3—figure supplement 2F). Moreover, in cells overexpressing SLC37A3, although a significant proportion of SLC37A3 remained un-glycosylated, only the glycosylated population of SLC37A3 interacted with ATRAID (Figure 3—figure supplement 2G), suggesting that the interaction with ATRAID is crucial for the expression of correctly modified SLC37A3.

Finally, we explored the mechanism by which the knockout of SLC37A3 and ATRAID conferred resistance to N-BPs. Given the predicted function of SLC37A3 as a transporter, we hypothesized that ATRAID and SLC37A3 transport N-BP molecules across the lipid bilayer to inhibit FDPS. Indeed, we observed that SLC37A3 resides on the membrane of vesicles in which internalized fluorescently-labeled zoledronate (AF647-ZLN) accumulates (Figure 4A), supporting its role as a transporter of N-BPs. This hypothesis is also consistent with our finding that the role of SLC37A3 and ATRAID in the mechanism of action of N-BPs is specific to the chemical properties of N-BPs. We implemented radioactive uptake assays to test this hypothesis. When we incubated wild-type, ATRAID^KO and SLC37A3^KO cells with radioactive ALN (³H-ALN) and measured total intracellular radioactivity, we observed no significant difference in whole-cell accumulation of radioactivity between the knockouts and wild-type cells (Figure 4B). As N-BP molecules accumulate in SLC37A3-positive vesicles and SLC37A3 localizes to lysosomes, we further hypothesized that N-BP molecules traffic to lysosomes and that SLC37A3 and ATRAID, together as a lysosomal complex, might function to release N-BP molecules from the lumen of lysosomes into the cytosol. This model predicts that the total amount of intracellular ³H-ALN will remain the same in wild-type, SLC37A3^KO and ATRAID^KO cells, but ³H-ALN will not be able to exit lysosomes in knockout cells. To detect this potential shift in the subcellular distribution of ³H-ALN in knockout cells, we used digitonin to selectively permeabilize the plasma membrane of ³H-ALN treated cells and generated a cytosolic fraction and a membranous fraction, which contained intact membrane-bound organelles (Figure 4—figure supplement 1A) (Liu and Fagotto, 2011). We observed that the distribution of radioactive signal changed from being primarily in the cytosolic fraction in wild-type cells to being predominantly in membranous fractions in SLC37A3^KO and ATRAID^KO cells (Figure 4C), suggesting that ³H-ALN cannot be released from membrane-bound organelles in knockout cells. As our model specifically predicts that ³H-ALN will be trapped in lysosomes in the absence of SLC37A3 or ATRAID, we affinity-purified lysosomes from ³H-ALN treated cells (Figure 4—figure supplement 1B–D) (Abu-Remaileh et al., 2017; Wyant et al., 2017) to assess the lysosomal accumulation of ³H-ALN. As our model predicted, we observed a significant enrichment of ³H-ALN in lysosomes purified from knockout cells compared to those from wild-type cells (Figure 4D). Additionally, consistent with the observation that ATRAID is required for the stable expression of SLC37A3, ATRAID^KO cells phenocopied SLC37A3^KO cells in these uptake assays. Taken together, our results suggest that N-BPs traffic to lysosomes after internalization through endocytosis, and SLC37A3 and ATRAID form a lysosomal transporter complex that releases N-BP molecules from the lumen of lysosomes into the cytosol.

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In summary, this study elucidates the route by which N-BPs enter the cytosol and inhibit their molecular target. As a recent study has proposed that patients who harbor a genetic variant of GGPS1 might be more prone to the side-effects of N-BP treatment (Roca-Ayats et al., 2017), it is possible that patients with variants of SLC37A3 or ATRAID, which are genes crucial for the action of N-BPs, might also exhibit non-canonical responsiveness to the drugs. Therefore, our results may bear significant relevance to the clinical applications of N-BPs.

All data generated or analysed during this study are included in the manuscript and supporting files. Source data files have been provided for the two CRISPRi screens shown in Figure 1 and its figure supplement.

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Author details

1. Zhou Yu

   1. Department of Molecular and Cellular Biology, Harvard University, Cambridge, United States
   2. Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States

   Contribution

   Conceptualization, Resources, Data curation, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing—original draft

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-3213-4583

2. Lauren E Surface

   1. Department of Molecular and Cellular Biology, Harvard University, Cambridge, United States
   2. Faculty of Arts and Sciences Center for Systems Biology, Harvard University, Cambridge, United States
   3. Department of Chemistry and Chemical Biology, Harvard University, Cambridge, United States
   4. Howard Hughes Medical Institute, Bethesda, United States

   Contribution

   Conceptualization, Data curation, Formal analysis, Validation, Investigation

   Competing interests

   No competing interests declared

3. Chong Yon Park

   Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, United States

   Contribution

   Resources, Investigation, Methodology

   Competing interests

   No competing interests declared

4. Max A Horlbeck

   1. Howard Hughes Medical Institute, Bethesda, United States
   2. Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, United States
   3. Center for RNA Systems Biology, University of California, San Francisco, San Francisco, United States

   Contribution

   Resources, Data curation, Software, Formal analysis, Methodology

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-3875-871X

5. Gregory A Wyant

   1. Howard Hughes Medical Institute, Bethesda, United States
   2. Whitehead Institute for Biomedical Research, Cambridge, United States
   3. Department of Biology, Massachusetts Institute of Technology, Cambridge, United States
   4. Koch Institute for Integrative Cancer Research, Cambridge, United States
   5. Broad Institute of MIT and Harvard, Cambridge, United States

   Contribution

   Conceptualization, Resources, Formal analysis, Investigation, Methodology

   Competing interests

   No competing interests declared

6. Monther Abu-Remaileh

   1. Howard Hughes Medical Institute, Bethesda, United States
   2. Whitehead Institute for Biomedical Research, Cambridge, United States
   3. Department of Biology, Massachusetts Institute of Technology, Cambridge, United States
   4. Koch Institute for Integrative Cancer Research, Cambridge, United States
   5. Broad Institute of MIT and Harvard, Cambridge, United States

   Contribution

   Conceptualization, Resources, Investigation, Methodology

   Competing interests

   No competing interests declared

7. Timothy R Peterson

   Division of Bone & Mineral Diseases, Department of Genetics, Institute for Public Health, Washington University School of Medicine, St. Louis, United States

   Contribution

   Conceptualization, Data curation, Formal analysis, Project administration

   Competing interests

   No competing interests declared

8. David M Sabatini

   1. Howard Hughes Medical Institute, Bethesda, United States
   2. Whitehead Institute for Biomedical Research, Cambridge, United States
   3. Department of Biology, Massachusetts Institute of Technology, Cambridge, United States
   4. Koch Institute for Integrative Cancer Research, Cambridge, United States
   5. Broad Institute of MIT and Harvard, Cambridge, United States

   Contribution

   Conceptualization, Resources, Supervision, Project administration

   Competing interests

   No competing interests declared

9. Jonathan S Weissman

   1. Howard Hughes Medical Institute, Bethesda, United States
   2. Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, United States
   3. Center for RNA Systems Biology, University of California, San Francisco, San Francisco, United States

   Contribution

   Conceptualization, Resources, Supervision, Project administration

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-2445-670X

10. Erin K O'Shea

    1. Department of Molecular and Cellular Biology, Harvard University, Cambridge, United States
    2. Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
    3. Faculty of Arts and Sciences Center for Systems Biology, Harvard University, Cambridge, United States
    4. Department of Chemistry and Chemical Biology, Harvard University, Cambridge, United States
    5. Howard Hughes Medical Institute, Bethesda, United States

    Contribution

    Conceptualization, Resources, Supervision, Funding acquisition, Validation, Writing—original draft, Project administration

    For correspondence

    osheae@hhmi.org

    Competing interests

    Chief Scientific Officer and a Vice President at the Howard Hughes Medical Institute, one of the three founding funders of eLife.

    "This ORCID iD identifies the author of this article:" 0000-0002-2649-1018

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